Encapsulation in Python: A Detailed Explanation with Coding Example

In Python object-oriented programming (OOP), encapsulation allows us control access to methods and variables, preventing accidental data changes. Encapsulation means bundling the data (attributes) and methods (functions) that operate on the data into a single unit. By default, everything in a class is public since Python doesn’t have strict access modifiers.

This blog will provide a detailed explanation of encapsulation in Python with coding examples.

Let’s first understand what is Encapsulation?

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What is Encapsulation?

Encapsulation means wrapping the data into a single unit. 

Let’s take an easy example of Encapsulation so you can easily understand the concept.

For Example – Imagine a tree. It has parts like roots, stem, branches, leaves, flowers, and fruits, and it performs functions like photosynthesis. Yet, we simply call it a “tree.” Similarly, encapsulation combines data and functions into a single unit in programming.

In Python, encapsulation helps us hide an object’s internal details and only show a specific way to interact with it.

By using encapsulation, we can:

1. Protect sensitive data from outside access.
2. Ensure that data is modified only through specific methods.
3. Control who can access the internal parts of a class.

Now, you may have a question in mind about the level of Access modifiers in Python.

Levels of Access Modifiers in Python

Python provides three levels of access modifiers for encapsulation:

1. Public Members: Public Members means Accessible from anywhere.
2. Protected Members: Protected Members Indicated by a single underscore (_,) meant to be accessed within the class and its subclasses.
3. Private Members: Private Members Indicated by a double underscore (__,) strictly restricts access to within the class only.

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How to Implement Encapsulation in Python

Let’s explore how encapsulation works in Python with a step-by-step coding example.

Example: Bank Account Class

In this example, we’ll create a simple “BankAccount” class with private and protected attributes and methods to manage balance and transactions.

Explanation of the Code

As you can see in this coding example – 

1. Public Member (owner): This attribute is accessible from outside the class, representing the account owner.
2. Protected Member (_balance): The balance attribute is protected by a single underscore _balance.

This means it’s meant for use within the class and isn’t recommended for direct access from outside.

III. Private Method (__apply_interest): The method __apply_interest is private, indicated by a double underscore (__) . 

This means it’s accessible only within the class and cannot be called from outside. Attempting to call it externally will result in an error.

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Why Use Encapsulation?

Encapsulation is mainly helpful in real-world applications, like:

• Protecting sensitive data: For example, preventing unauthorized access to a user’s bank account balance.
• Maintaining control: Using encapsulation ensures that attributes and methods are accessed and modified as intended.
• Reducing complexity: With encapsulation, the internal details of an object are hidden, making it easier to understand and manage code at a higher level.

Advantages of Encapsulation

1. Data Hiding: Sensitive data is hidden and accessed only through specific methods.
2. Enhanced Security: Reduces risk of accidental data modification.
3. Modularity: Class code can be reused without exposing sensitive details.
4. Flexibility: Allows making changes to restricted attributes and methods without affecting external code.

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What is property encapsulation in Python?

Another way to achieve encapsulation in Python is by using properties. Properties allow you to create special methods called getters and setters for an attribute. 

This allows you to control how the attribute is accessed and modified more easily.

Example with Properties

Explanation of Properties Example

1. The @property decorator is used to define a price property that provides controlled access to the _price attribute.
2. The @price.setter decorator defines a method that validates any new value assigned to price.

This example demonstrates how encapsulation can provide safe data access and control over data modification.

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Conclusion

I hope you get a better understanding of Encapsulation in Python.

• Encapsulation is important in Python Programming.
• It helps hide data to keep your code secure and organized.
• You can protect data and control who can access it.
• It keeps your code clean and easy to manage, test, and update.
• Python’s tools for access control and properties make encapsulation easy to use.

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FAQ’s

What are the four types of encapsulation?

The four types are – 

1. Data encapsulation  
2. Method encapsulation
3. Class encapsulation
4. Interface encapsulation

What is polymorphism and encapsulation in Python?

Polymorphism allows objects to take on many forms, allowing different classes to use the same method names, while encapsulation restricts direct access to data by hiding it within classes.

What are methods in encapsulation

Encapsulation methods like getters and setters manage access to private attributes, providing controlled ways to read and update data.

When to use encapsulation?

Use encapsulation to protect sensitive data, control data access, and simplify code maintenance by creating secure, modular classes.